References

[BLB+13]

Lars Buitinck, Gilles Louppe, Mathieu Blondel, Fabian Pedregosa, Andreas Mueller, Olivier Grisel, Vlad Niculae, Peter Prettenhofer, Alexandre Gramfort, Jaques Grobler, Robert Layton, Jake Vanderplas, Arnaud Joly, Brian Holt, and Gaël Varoquaux. API design for machine learning software: experiences from the scikit-learn project. In Workshop on Languages for Data Mining and Machine Learning at ECMLPKDD 2013. September 2013. URL: http://arxiv.org/abs/1309.0238.

[DK04]

Mukund Deshpande and George Karypis. Item-based Top-N recommendation algorithms. ACM Transactions on Information Systems, 22(1):143–177, January 2004. URL: https://doi.org/10.1145/963770.963776, doi:10.1145/963770.963776.

[EK19]

Michael D Ekstrand and Joseph A Konstan. Recommender systems notation. Technical Report 177, Boise State University, 2019. URL: https://arxiv.org/abs/1902.01348, doi:10.18122/cs\_facpubs/177/boisestate.

[ELKR11]

Michael D Ekstrand, Michael Ludwig, Joseph A Konstan, and John T Riedl. Rethinking the recommender research ecosystem: reproducibility, openness, and LensKit. In Proceedings of the Fifth ACM Conference on Recommender Systems, RecSys '11, 133–140. ACM, 2011. URL: http://doi.acm.org/10.1145/2043932.2043958, doi:10.1145/2043932.2043958.

[GWZE19]

Aditya Grover, Eric Wang, Aaron Zweig, and Stefano Ermon. Stochastic optimization of sorting networks via continuous relaxations. In Proceedings of the Seventh International Conference on Learning Representations. March 2019. URL: https://openreview.net/forum?id=H1eSS3CcKX.

[HKV08]

Y Hu, Y Koren, and C Volinsky. Collaborative filtering for implicit feedback datasets. In 2008 Eighth IEEE International Conference on Data Mining, 263–272. ieeexplore.ieee.org, December 2008. URL: http://dx.doi.org/10.1109/ICDM.2008.22, doi:10.1109/ICDM.2008.22.

[JarvelinKekalainen02]

Kalervo Järvelin and Jaana Kekäläinen. Cumulated gain-based evaluation of IR techniques. ACM Transactions on Information Systems, 20(4):422–446, October 2002. URL: https://doi.org/10.1145/582415.582418, doi:10.1145/582415.582418.

[KV97]

Paul B Kantor and Ellen Voorhees. Report on the TREC-5 confusion track. In The Fifth Text REtrieval Conference (TREC-5). October 1997. URL: http://trec.nist.gov/pubs/trec5/t5_proceedings.html.

[TakacsPilaszyT11]

Gábor Takács, István Pilászy, and Domonkos Tikk. Applications of the conjugate gradient method for implicit feedback collaborative filtering. In Proceedings of the Fifth ACM Conference on Recommender Systems, RecSys '11, 297–300. New York, NY, USA, October 2011. Association for Computing Machinery. URL: https://doi.org/10.1145/2043932.2043987, doi:10.1145/2043932.2043987.

[TDV21]

Yan-Martin Tamm, Rinchin Damdinov, and Alexey Vasilev. Quality metrics in recommender systems: do we calculate metrics consistently? In Fifteenth ACM Conference on Recommender Systems, RecSys '21, 708–713. New York, NY, USA, September 2021. Association for Computing Machinery. URL: https://doi.org/10.1145/3460231.3478848, doi:10.1145/3460231.3478848.

[ZWSP08]

Yunhong Zhou, Dennis Wilkinson, Robert Schreiber, and Rong Pan. Large-Scale parallel collaborative filtering for the netflix prize. In Algorithmic Aspects in Information and Management, 337–348. Springer Berlin Heidelberg, 2008. URL: http://dx.doi.org/10.1007/978-3-540-68880-8_32, doi:10.1007/978-3-540-68880-8\_32.